We identified a 14-year-old boy with immunodeficiency, intellectual disability, short stature, dysmorphic features, hearing impairment, and leukemia early in life, where whole genome sequencing (WGS) detected a homozygous ultra-rare variant in FLCN. The variant is homozygous missense fitting to autosomal recessive inheritance and unique to the Swedish population. Previously reported knock-out models show that folliculin is an important protein in the regulation of diverse pathways in different tissues during development and homeostasis. A phenotypic comparison of our patient to these models showed noticeable similarities suggesting that a homozygous variant in FLCN could result in a viable complex syndrome. The preliminary data on expression analysis based on ddPCR of selected genes showed increased expression of key genes which was a finding that was similar to what was observed in the conditional knockout models. Therefore, in this project, we aim to uncover how the identified FLCN variant can lead to an autosomal recessive complex syndrome. We want to investigate further the up and downregulated key pathways such as mTOR pathway and lysosomal biogenesis pathway in patient derived fibroblasts by comparing the expressions levels to the control healthy fibroblasts. Therefore we will perform RNAseq and identify the differentially expressed protein coding genes. Additionally, we have RNA from lymphocytes of the patient, healthy brother and the parents. As the patient has immunodeficiency we also want to check the expression of key genes in these cells. Upon completion of this project, new knowledge will be gained on folliculin, and disease mechanisms of different FLCN phenotypes and eventually we will describe a novel FLCN-related syndrome. The NAISS SENS project will be used to analyze the RNA-seq data from the patient and control fibroblasts (total number of samples =16). We will use open-source tools like DESeq2, edgeR, cuffdiff and limma to analyze the differential expression in the samples. After the project is completed, the raw data and output files will be stored for long-term storage in our local servers at the department (KI MMK). The results will be published in an open-access journal.